1. Field of the Invention
The present invention relates to multiple value image filtering devices which can be used in an image scanner capable of reading multiple optical density values of picture images and, more specifically, to such multiple value image filtering devices designed to eliminate noise from multiple-valued picture image data.
2. Discussion of the Related Art
Conventional picture image reading devices read picture image information on original documents and represent that information as picture image data capable of assuming multiple values. Such image reading devices are used for reproducing the lighting and shading of photographs and other images. Conventional picture reading devices, however, often produce picture image data having black or white dots in parts of the reproduced picture images. According to one description, the dots resemble "parched sesame seeds mixed with salt." An example of these dots is shown in area 11 in FIG. 1.
These dots, which are called "noise," occur because of the complicated interaction of various factors such as fluctuations in the output of the individual pixels themselves in the image sensor, a local lack of uniformity in the exposure of the picture images to light in an exposure unit, or a non-constant moving speed of the scanning unit in relation to the original sheet.
This noise causes considerable deterioration of the quality of reproduced picture images similar to the deterioration in a television system in which noise appears as snow grains on the television screen.
FIG. 2 illustrates the construction of a conventional multiple value image filtering device for removing such noise. This device is provided with a linear low pass filter 13 and is designed to receive multiple value picture image data 14 at its input. Linear low pass filter 13 sequentially receives segments of multiple value picture image data for individual pixels and inhibits the passage of those segments of the picture image data having a sharp change in density. A sharp change, which is manifested by segments in a high frequency range, indicates noise. Multiple value picture image data 15 without noise can be obtained from the output of linear low pass filter 13.
If the cut-off frequency of low pass filter 13 is set too high, filter 13 permits image data containing noise components to pass through as normal picture image data without modification. If this occurs, the noise has not been completely removed from the conventional multiple value image filtering device.
The lower the cut-off frequency level is set, the more thoroughly the filtering device eliminates noise. Hence, for eliminating noise only, the cut-off frequency should be as low as possible. The lower the cut-off frequency, however, the more probable it will be that components of proper picture images are also eliminated. If proper image data components are eliminated, the reproduced picture images are dull and lack adequate definition, especially in areas in which a white background makes a transition into black characters or vice versa.
The effect of too much filtering can be seen by reference to FIG. 3(a) and FIG. 3(b). FIG. 3(a) illustrates the state of multiple value picture image data output in 64 chromatic grades from a scanner sensing one line of a picture image. On the vertical axis, the value "0" represents the state with the highest degree of black color while "63" represents the state with the highest degree of white color. The horizontal axis represents calibrated positions on the main scanning direction, the main scanning width being divided into 100 equal parts. The relationship between the vertical and horizontal axes is same in FIG. 3(b).
When the multiple value picture image data shown in FIG. 3(a) are filtered through the linear low pass filter 13 in FIG. 2, the resulting picture images will be as shown in FIG. 3(b). As the result of eliminating the high frequency components, the picture images show a density waveform that is flattened without picture image information where considerable changes in density occur. This effect is present regardless of whether the eliminated picture image information represents noise. The result is that the density in that area is reduced and approaches the density in the adjacent parts so that the difference in density is rendered less conspicuous. Consequently, the contour of the picture images loses sharpness and the shades of the picture images become indistinct.